Zero-dimensional Model Research Articles

Model-Based Dynamic Performance Simulation of a Microturbine Using Flight Test Data

Microturbines can be used not only in models and education but also to propel UAVs. However, their wider adoption is limited by their relatively low efficiency and durability. Validated simulation models are required to monitor their performance, improve their lifetime, and to design engine control systems. This study aims at developing a numerical model of a micro gas turbine intended for prediction and prognostics of engine performance. To build a reliable zero-dimensional model, the available compressor and turbine maps were scaled to the available test bench data with the least squares method, to meet the performance of the engine achieved during bench and flight tests. A steady-state aeroengine model was implemented in the Gas turbine Simulation Program (GSP) and was compared with experimental operating points. The selected flight data were then used as input for the transient engine model. The exhaust gas temperature (EGT) and fuel flow were chosen as the two key parameters to validate the model, comparing the numerical predicted values with the experimental ones. The observed difference between the model and the flight data was lower than 3% for both EGT and fuel flow.

Development of semi-empirical soot emission model for a CI engine

Soot is one of the main harmful emissions of diesel engines that is mainly generated in the reacting fuel jet of diesel injection. Over 99% of the engine-out soot can be filtered by a diesel particulate filter (DPF). However, when the soot load of the DPF is high, a regeneration process that oxidizes the accumulated soot reduces fuel economy. A real-time soot estimation model can contribute to real-time feedback soot control under transient conditions to minimize the engine-out soot emission and frequency of DPF regeneration.A zero-dimensional engine-out soot estimation model for a diesel engine is developed in this study. The semi-empirical soot model considers both the formation and oxidation of soot. In the model, soot formation was correlated with the cross-sectional average equivalence ratio at the lift-off length of the fuel spray. The equivalence ratio at the lift-off length is an indicator of how much air and vaporized fuel are mixed as the fuel reaches the reaction zone. The mass of the injected fuel and combustion duration were also correlated with soot formation. The Nagle and Strickland-Constable mechanism, which calculates the soot oxidation rate was correlated with the soot oxidation in this study. The results of the soot estimation showed an R2 of 0.901 and root mean square error of 10.8 mg/m3 for steady-state experimental cases. The engine-out soot model was also combined with the in-cylinder pressure model proposed by the authors, and validated through the transient Worldwide Harmonized Light Vehicles Test Cycle (WLTC) mode. The estimates agreed with the measured soot, with an accumulated soot error of approximately 6% during the WLTC, even without using an in-cylinder pressure sensor. The soot model developed in this study can help minimize tailpipe-out soot emissions and improve fuel economy by influencing the real-time feedback control during transient and frequent DPF regeneration.

Modeling of heat leak effect in round trip efficiency for Brayton pumped heat energy storage with liquid media, by cooling and heating of the reservoirs tanks

For a pumped heat energy storage technology with commercial solar salt and a cold fluid such as methanol, the performance in long times of the Brayton like model associated to the losses of the four tanks (two high temperature units and two low temperature units) was studied. A round trip efficiency evaluation model linked with the heat leak coefficient was proposed for the sensible storage tanks, considering the losses for each face exposed to the environment. The different energy leaks and temperatures in the tanks were calculated for hourly climatic fluctuations during a reference year for a reference city. A zero-dimensional model was developed where radiation (direct and diffuse), convection and conduction effects were considered. The obtained results showed that for long periods, time and insulation thickness have a significant influence on the performance of the technology for long periods. For Brayton pumped heat energy storage technology with solar salts the round trip efficiency, which can be reduced daily by 0.4% even for a considerable insulation thickness of around 10% of the tank diameter. Winter–summer climatic conditions do not show a significant difference for tanks at higher temperatures, but as the temperature decreases, the effect becomes more visible but not decisive for the performance of the technology. The relatively high crystallization point of solar salt represents a significant solidification risk that limits the operation of the PHES technology during waiting periods for a surplus power to charge the system.

Temperature-dependent ion chemistry in nanosecond discharge plasma-assisted CH4 oxidation

Ion chemistry with temperature evolution in weakly ionized plasma is important in plasma-assisted combustion and plasma-assisted catalysis, fuel reforming, and material synthesis due to its contribution to plasma generation and state transition. In this study, the kinetic roles of ionic reactions in nanosecond discharge (NSD) plasma-assisted temperature-dependent decomposition and oxidation of methane are investigated by integrated studies of experimental measurements and mathematical simulations. A detailed plasma chemistry mechanism governing the decomposition and oxidation processes in a He/CH4/O2 combustible mixture is proposed and studied by including a set of electron impact reactions, reactions involving excited species, and ionic reactions. A zero-dimensional model incorporating the plasma kinetics solver ZDPlasKin and the combustion chemical kinetics solver CHEMKIN is used to calculate the time and temperature evolution of the ion density. Uncertainty analysis of ionic reactions on key species generation is conducted by using different referenced data, and insignificant sensitivity is found. The numerical model is consistent with experimental data for methane consumption and generation of major species including CO, CO2, and H2. By modeling the temporal evolution of key ions, it is observed that O2 + presents the largest concentration in the discharge stage, followed by CH4 +, CH3 +, and CH2 +, which is in accordance with the traditional ion chemistry in hydrocarbon flames and agrees well with molecular-beam mass spectrometer investigations. The path flux shows that the concentrations of key species, including electrons, O, OH, H, O(1D), O2(a1Δg), O2 +, CH3 +, and CH4 +, change within 1–2 orders of magnitude and that the transition from a homogeneous state to a contracted/constricted state does not occur. The path flux and sensitivity analysis reveal the significant roles of cations in the stimulation of active radical generation, including CH, O, OH, and O(1D), thus accelerating methane oxidation. This work provides a deep insight into the ion chemistry of temperature-dependent plasma-assisted CH4 oxidation.

A model based investigation of evaporative cooling for polymer electrolyte fuel cells – Stack level analysis

Conventional cooling systems of polymer electrolyte fuel cells are responsible for a significant share of stack and system volume, mass and cost. Evaporative cooling shows the potential to overcome these hurdles by simplifying the design of bipolar plates and eliminating the need for an external humidifier. Thus, evaporative cooling can significantly contribute towards reaching the DOE fuel cell system power density target of 850 W/L. This paper investigates the potentials and limits of evaporative cooling at stack level. For this, a zero-dimensional model has been developed, incorporating mass and energy balances as well as electrochemistry and evaporation. Main findings show that evaporative cooling is feasible over a wide range of operating conditions. The cooling performance is a function of temperature, gas pressures and stoichiometric ratios, where the temperature shows the largest leverage. A feasible operating window is proposed, which is slightly shifted towards higher temperatures (80–95 °C), lower pressures (100–200 kPa) and higher cathode stoichiometric ratios (>1.5) compared to conventional fuel cells. A slight decrease in electrochemical performance (ca. 3% at 1.5 A/cm 2 ) is easily compensated by the volume and weight saving potential of up to 30% and thus substantially reduced cost. • Potentials and limits of evaporative cooling for PEFC are analyzed. • A zero-dimensional fuel cell stack model is developed. • Optimal operating conditions for evaporative cooling are quantified. • An operating window for evaporative cooling is proposed. • The high mass, volume and cost saving potential of evaporative cooling is proven.

Reconciling models of interfacial state kinetics and device performance in organic solar cells: impact of the energy offsets on the power conversion efficiency.

Achieving the simultaneous increases in the open circuit voltage (Voc), short circuit current (Jsc) and fill factor (FF) necessary to further increase the power conversion efficiency (PCE) of organic photovoltaics (OPV) requires a unified understanding of how molecular and device parameters affect all three characteristics. In this contribution, we introduce a framework that for the first time combines different models that have been used separately to describe the different steps of the charge generation and collection processes in OPV devices: a semi-classical rate model for charge recombination processes in OPV devices, zero-dimensional kinetic models for the photogeneration process and exciton dissociation and one-dimensional semiconductor device models. Using this unified multi-scale model in conjunction with experimental techniques (time-resolved absorption spectroscopy, steady-state and transient optoelectronic measurements) that probe the various steps involved in charge generation we can shed light on how the energy offsets in a series of polymer: non-fullerene devices affect the charge carrier generation, collection, and recombination properties of the devices. We find that changing the energy levels of the donor significantly affects not only the transition rates between local-exciton (LE) and charge-transfer (CT) states, but also significantly changes the transition rates between CT and charge-separated (CS) states, challenging the commonly accepted picture of charge generation and recombination. These results show that in order to obtain an accurate picture of charge generation in OPV devices, a variety of different experimental techniques under different conditions in conjunction with a comprehensive model of processes occurring at different time-scales are required.

Enhanced Physics-Constrained Deep Neural Networks for Modeling Vanadium Redox Flow Battery

Numerical modeling and simulation have become indispensable tools for advancing a comprehensive understanding of the underlying mechanisms and cost-effective process optimization and control of flow batteries. In this study, we propose an enhanced version of the physics-constrained deep neural network (PCDNN) approach [1] to provide high-accuracy voltage predictions in the vanadium redox flow batteries (VRFBs). The purpose of the PCDNN approach is to enforce the physics-based zero-dimensional (0D) VRFB model in a neural network to assure model generalization for various battery operation conditions. Limited by the simplifications of the 0D model, the PCDNN cannot capture sharp voltage changes in the extreme SOC regions. To improve the accuracy of voltage prediction at extreme ranges, we introduce a second (enhanced) DNN to mitigate the prediction errors carried from the 0D model itself and call the resulting approach enhanced PCDNN (ePCDNN). By comparing the model prediction with experimental data, we demonstrate that the ePCDNN approach can accurately capture the voltage response throughout the charge--discharge cycle, including the tail region of the voltage discharge curve. Compared to the standard PCDNN, the prediction accuracy of the ePCDNN is significantly improved. The loss function for training the ePCDNN is designed to be flexible by adjusting the weights of the physics-constrained DNN and the enhanced DNN. This allows the ePCDNN framework to be transferable to battery systems with variable physical model fidelity.

Parameter Identification of DOC Model Based on Variable Forgetting Factor Least Squares

In diesel engine after-treatment control technology, the accurate real-time control of Diesel Oxidation Catalyst (DOC) outlet temperature is an important topic. To find a high-precision parameter identification algorithm for the DOC system, this paper establishes zero-dimensional (0D) and one-dimensional (1D) mathematical models of DOC, introduces Variable Forgetting Factor Least Squares(VFFRLS) and Nonlinear Least Squares parameter identification for comparison and analysis. The results show that the 0D determination coefficient R-square of Nonlinear Least Squares parameter identification results is around 0.9, the root mean square error (RSME) mean is 23.682, the R-square of 1D is mostly less than 0.9, and the mean value of RSME is 32.649; The R-square of VFFRLS algorithm is 1, and the RSME is below 0.02. Therefore, the VFFRLS algorithm is more suitable for the parameter identification of the DOC temperature model.

A Spectral Survey of CH3CCH in the Hot Molecular Core G331.512-0.103

Abstract A spectral survey of methyl acetylene (CH3CCH) was conducted toward the hot molecular core/outflow G331.512-0.103. Our APEX observations allowed the detection of 41 uncontaminated rotational lines of CH3CCH in the frequency range between 172 and 356 GHz. Through an analysis under the local thermodynamic equilibrium assumption, by means of rotational diagrams, we determined T exc = 50 ± 1 K, N(CH3CCH) = (7.5 ± 0.4) × 1015 cm2, X[CH3CCH/H2] ≈ (0.8–2.8) × 10−8, and X[CH3CCH/CH3OH] ≈ 0.42 ± 0.05 for an extended emitting region (∼10″). The relative intensities of the K = 2 and K = 3 lines within a given K-ladder are strongly negatively correlated to the transitions’ upper J quantum number (r = −0.84). Pure rotational spectra of CH3CCH were simulated at different temperatures, in order to interpret this observation. The results indicate that the emission is characterized by a nonnegligible temperature gradient with upper and lower limits of ∼45 and ∼60 K, respectively. Moreover, the line widths and peak velocities show an overall strong correlation with their rest frequencies, suggesting that the warmer gas is also associated with stronger turbulence effects. The K = 0 transitions present a slightly different kinematic signature than the remaining lines, indicating that they might be tracing a different gas component. We speculate that this component is characterized by lower temperatures and therefore larger sizes. Moreover, we predict and discuss the temporal evolution of the CH3CCH abundance using a two-stage zero-dimensional model of the source constructed with the three-phase Nautilus gas-grain code.

Modeling and performance analysis of diesel engine considering the heating effect of blow-by on cylinder intake gas

Recently, the stringent international regulations on ship energy efficiency and NOx emissions from ocean-going ships make energy conservation and emission reduction be the theme of the shipping industry. Due to its fuel economy and reliability, most large commercial vessels are propelled by a low-speed two-stroke marine diesel engine, which consumes most of the fuel in the ship. In the present work, a zero-dimensional model is developed, which considers the blow-by, exhaust gas bypass, gas exchange, turbocharger, and heat transfer. Meanwhile, the model is improved by considering the heating effect of the blow-by gas on the intake gas. The proposed model is applied to a MAN B&W low-speed two-stroke marine diesel engine and validated with the engine shop test data. The simulation results are in good agreement with the experimental results. The accuracy of the model is greatly improved after considering the heating effect of blow-by gas. The model accuracy of most parameters has been improved from within 5% to within 2%, by considering the heating effect of blow-by gas. Finally, the influence of blow-by area change on engine performance is analyzed with considering and without considering the heating effect of blow-by.

A spatiotemporally resolved infection risk model for airborne transmission of COVID-19 variants in indoor spaces

The classic Wells-Riley model is widely used for estimation of the transmission risk of airborne pathogens in indoor spaces. However, the predictive capability of this zero-dimensional model is limited as it does not resolve the highly heterogeneous spatiotemporal distribution of airborne pathogens, and the infection risk is poorly quantified for many pathogens. In this study we address these shortcomings by developing a novel spatiotemporally resolved Wells-Riley model for prediction of the transmission risk of different COVID-19 variants in indoor environments. This modelling framework properly accounts for airborne infection risk by incorporating the latest clinical data regarding viral shedding by COVID-19 patients and SARS-CoV-2 infecting human cells. The spatiotemporal distribution of airborne pathogens is determined via computational fluid dynamics (CFD) simulations of airflow and aerosol transport, leading to an integrated model of infection risk associated with the exposure to SARS-CoV-2, which can produce quantitative 3D infection risk map for a specific SARS-CoV-2 variant in a given indoor space. Application of this model to airborne COVID-19 transmission within a hospital ward demonstrates the impact of different virus variants and respiratory PPE upon transmission risk. With the emergence of highly contagious SARS-CoV-2 variants such as the Delta and Omicron strains, respiratory PPE alone may not provide effective protection. These findings suggest a combination of optimal ventilation and respiratory PPE must be developed to effectively control the transmission of COVID-19 in healthcare settings and indoor spaces in general. This generalised risk estimation framework has the flexibility to incorporate further clinical data as such becomes available, and can be readily applied to consider a wide range of factors that impact transmission risk, including location and movement of infectious persons, virus variant and stage of infection, level of PPE and vaccination of infectious and susceptible individuals, impacts of coughing, sneezing, talking and breathing, and natural and mechanised ventilation and filtration.

Analysis and optimization for multi-stack vanadium flow battery module incorporating electrode permeability

The large-scale all-vanadium flow battery module is commonly formed by a number of hydraulically parallel connected stacks. The existence of permeability difference in applicated electrode is supposed to be of great influential on module performance. Hence in this paper, the electrode permeability is firstly measured via a self-designed device, followed by an in-depth analysis of its effects by a zero-dimensional dynamic model for multi-stack flow battery module on the basis of mass balance. The simulation results depicted that the permeability variations can notably influence the flow rate, pump loss and overall efficiency for stacks, as well as the voltage uniformity for electrically series connected modules. Besides, the performance, especially the capacity, of electrically series-parallel hybrid multi-stack module can be significantly increased by arranging the stacks with similar electrode permeability in the same branch. In addition, increasing the flow rate, particularly by individual control mode can further increase the module capacity with an acceptably additional efficiency loss. The present study offers not only a full understanding of cardon felt permeability, but also a cost-effective way to evaluate the module performance. • The permeability of applicated electrodes is obtained by self-designed device. • A zero-dimensional module model incorporating electrode permeability is developed. • The effect of electrode permeability on multi-stack flow battery module is revealed. • Charging capacity can be improved by optimizing module layout and stack flow rate. • Studies on electrode permeability are beneficial to properly engineer multi-stack module.

Enhancement of the ion flux to the substrate through high-voltage biasing in an electron cyclotron resonance plasma and its application to high-speed deposition of conductive carbon film

A method for enhancing ion flux to the substrate via high-voltage pulse biasing is investigated in an electron cyclotron resonance plasma. When high-voltage pulse biases above 500 V are applied to the stage, an increase in the stage current is observed, especially in the case of diverging magnetic field configurations in front of the bias stage. The growth and decay time constants of the plasma density and emission intensity are evaluated using a time-resolved Langmuir probe and emission spectroscopy while the pulse is on, and the enhancement of the ionization rate during the bias application is estimated using the zero-dimensional global model. The estimated density enhancement from the model is in good agreement with the measured one. From the numerical simulation of secondary electron trajectory, it is concluded that the electron confinement from the magnetic field is the key factor in plasma density enhancement during stage biasing. Using the high-density plasma produced by the bias voltage, conductive carbon is deposited at a high deposition rate of ∼4 nm s−1.

Controlled growth of silicon particles via plasma pulsing and their application as battery material

The use of silicon nanoparticles for lithium-ion batteries requires a precise control over both their average size and their size distribution. Particles larger than the generally accepted critical size of 150 nm fail during lithiation because of excessive swelling, while very small particles (<10 nm) inevitably lead to a poor first cycle coulombic efficiency because of their excessive specific surface area. Both mechanisms induce irreversible capacity losses and are detrimental to the anode functionality. In this manuscript we describe a novel approach for enhanced growth of nanoparticles to ∼20 nm using low-temperature flow-through plasma reactors via pulsing. Pulsing of the RF power leads to a significant increase in the average particle size, all while maintaining the particles well below the critical size for stable operation in a lithium-ion battery anode. A zero-dimensional aerosol plasma model is developed to provide insights into the dynamics of particle agglomeration and growth in the pulsed plasma reactor. The accelerated growth correlates with the shape of the particle size distribution in the afterglow, which is in turn controlled by parameters such as metastable density, gas and electron temperature. The accelerated agglomeration in each afterglow phase is followed by rapid sintering of the agglomerates into single-crystal particles in the following plasma-on phase. This study highlights the potential of non-thermal plasma reactors for the synthesis of functional nanomaterials, while also underscoring the need for better characterization of their fundamental parameters in transient regimes.

Low-cost lumped parameter modelling of hydrogen storage in solid-state materials

A low-cost lumped parameter model (LPM) is developed to simulate hydrogen storage in solid-state materials. The proposed LPM is a zero-dimensional model based on an analogous transient thermal resistance network that considers the whole storage system as a resistor–capacitor (RC) circuit with a current source. Combined with the mass conservation, sorption kinetics, and equation of state, the LPM is capable of predicting key thermofluidic quantities of the storage system, such as the storage bed temperature and pressure, hydrogen fraction and flowrate, and storage tank temperature. To test the applicability of the LPM, chemisorptive (Mg and LaNi5) and physisorptive (activated carbon) solid-state materials are simulated for adsorption and desorption processes. For both material types, LPM achieves predictive accuracies comparable to three-dimensional computational fluid dynamics (CFD) simulations, especially for hydrogen fraction and storage times (with maximum errors less than 9.6%), for a fraction of the computational cost (23,734 times lower memory requirement and 126 times faster calculation time). In addition, several formulations of the bed thermal resistance are proposed and discussed in terms of their impact on the accuracy of the LPM predictions. For slender cylindrical tanks, an equivalent annulus formula achieves the best balance of simplicity and accuracy.

The exploration of bypass matching limitation and mechanisms in a double bypass engine compression system

In order to clarify the influence of bypass configuration on the variation range of the bypass ratio in a variable cycle engine, as well as revealing the effect of bypass ratio adjustment on the engine aerodynamic performance, an integrated zero-dimensional bypass model is established based on a double bypass engine compression system. The bypass model employs the control volume method and is validated by the bypass flow database which is established using a novel high-accuracy simplified bypass system computational method. By relating the model parameters to the engine component operation points, evaluation of the bypass aerodynamic performance in the real engine environment is realized, and the feature parameters decisive for the bypass matching characteristic are proposed. The operating range of the bypass system is then disclosed using the bypass model, which is instructive for the aerodynamic design of the whole compression system. Results show that to increase the total bypass ratio, one can decrease bypass backpressure, reduce the core driven fan stage (CDFS) total pressure ratio, increase the mode selector valve (MSV) opening angle or open up the forward variable area bypass injector (FVBAI). Different methods tend to influence the bypass matching characteristics differently. The non-monotonicity characteristic of the dividing flow loss around the MSV will induce a multi-solution zone for the double bypass configuration and make it difficult to diagnose the system operating state. Moreover, the inner bypass will reach the critical condition before the outer bypass, yet the supercritical condition is not recommended as it requires unique bypass geometry and will bring about high flow loss.

Investigation of important semi-empirical heat transfer models for a natural gas-fueled HCCI engine

Homogeneous charge compression ignition engine is a promising alternative to traditional internal combustion engines mainly due to its high thermal efficiency, low NOx, and soot emissions. Heat transfer from gases to the combustion chamber walls has a significant effect on the combustion, performance, and formation of pollutants in HCCI engines. This study used the zero-dimensional single-zone model coupled with detailed chemical kinetics to compare the accuracy of different semi-empirical heat transfer models In the single-zone model, the heat transfer models including, Annand, Woschni, Hohenberg, Assanis, and Hensel were evaluated in a wide working range of a natural gas-fueled HCCI engine. To the best of the author’s knowledge, the heat transfer has not been experimentally measured in an HCCI engine fueled with natural gas. Therefore, in this investigation, a three-dimensional computational fluid dynamics model with detailed chemical kinetics has been considered to study the heat transfer models. The validation results indicated that the 3D model could accurately estimate the engine-out parameters. Besides, the response surface method was employed to evaluate the impacts of the engine operating parameters, including the intake pressure (1, 1.25, and 1.5 bars), equivalence ratio (0.3, 0.5, and 0.7), and engine speed (800, 1100, and 1400 rpm) on the heat flux as a response factor. The results indicated that Assanis and Hohenberg heat transfer models had the best performance in estimating the heat transfer of an HCCI engine with an average error of 14.3% and 16.3%, respectively, compared with the 3D model.

Modeling and experimental validation of a triple-screw pump for internal combustion engine cooling

• Development of the mathematical model of a triple-screw pump. • Idler screws without a dedicated support determine complex friction phenomena. • Experimental assessment of volumetric and mechanical performances. • Maximum global efficiency achieved equal to 70% • 8.2% efficiency improvement on ICE cooling application compared to centrifugal pump. Internal Combustion Engine (ICE) cooling system is receiving a new technological interest for the influence it has on primary harmful and CO2 emissions reduction. Improvements on pump efficiency are requested to reduce its required energy during real on-the-road operation. Present technology always considers centrifugal pumps whose efficiency is highly dependent on rotational speed: consequently, pumps designed to have a very high efficiency at design point, show poor performances during usual operation, wasting energy. This study aims to assess the screws pumps potentiality to substitute the traditional centrifugal pumps for engine cooling. The main advantage is that positive displacement pumps have an efficiency ideally non-dependent on rotational speed, flow rate and head delivered, so having requirements that can fit more the engine cooling features. A novel comprehensive zero-dimensional mathematical model has been formulated to predict the performances of triple-screw pumps, in terms of volumetric, indicated and mechanical efficiency as a function of main operating conditions of the pump. A wide experimental activity has been done, resulting in a good agreement with predictions in spite of the manufacture of the pump, which privileges a low-cost solution as it is requested for the specific sectors of application. The model, once experimentally validated, demonstrates a high validity as virtual platform for a model-based design, thus offering the possibility to include design aspects particularly suitable for engine cooling systems. At last, by simulating the World Harmonized Transient Cycle on an F1C IVECO 3l engine, the triple-screw pump shows an average efficiency about 8% greater than that of the centrifugal pump, leading to an energy saving equal to 18.5%. This result leads the way to the use of screws pumps also in the engine cooling system of an on-the-road vehicle, which could represent a new potential application, never considered before.

Zero-dimensional turbulence modeling of a spark ignition engine in a Miller cycle « Dethrottling » approach using a variable valve timing system

• A complete 0D model with in-cylinder aerodynamic prediction and turbulent combustion is proposed. • Analytical calculation of quantities reduces the cost and time of the predictions. • The effect of a VVT system on the performance of an EIVC Miller cycle engine is investigated. • Reduction in pumping losses results in benefits of up to 1% over a wide range of engine loads. The Miller cycle, using an early inlet valve closing, can significantly improve the overall efficiency of a spark ignition engine during partial load operations. The shorter valve intake event minimizes the need for throttling the air and so reduces the pumping losses. This method is known as “dethrottling”. Indeed, the use of a variable valve lift system makes it possible to combine two different cam profiles in an engine, one for the full load operations and one for the partial loads. The benefits of this strategy, combined with a variable valve timing (VVT) system, will be explored using a new 0D model. This model can take into account the strong changes of in-cylinder turbulence generated by the VVT and their effects on the combustion. Efforts have been made to reduce the model's reliance on external inputs. Therefore, analytical calculations of quantities, such as the flame radius, have been favored. The Miller cycle can lead to indicated efficiencies around 44% and the addition of a VVT system can improve the overall efficiency up to 1% over a wide range of engine loads.

Measurement and modeling of the near-nozzle ambient gas entrainment of high-pressure diesel sprays

The ambient gas entrainment of the diesel spray affects the fuel evaporation and the subsequent ignition and pollutant formation processes. In this work, the gas entrainment process in the breakup length of the diesel spray is investigated by the high-speed micro-particle tracking velocimetry (micro-PTV) technique. With the high frequency of the micro-PTV technique of 28 kHz, the images of the tracer particle and the spray boundary are captured simultaneously in one shot. The experimental results show that during the quasi-steady and transient states, the gas entrainment velocity increases as the injection pressure rises. However, the ambient density has no impact on the entrainment velocity in the breakup length. During the quasi-steady state, the local gas entrainment rate shows a linear dependence on the spray axial distance (z), and the cumulative gas entrainment rate shows a z2 dependence. A theoretical zero-dimensional (0-D) model is proposed to estimate the cumulative gas entrainment rate during the quasi-steady state, and it is validated with the experimental results. The results suggest that the gas entrainment in the breakup length is probably dominated by the breakup process of the liquid core.